{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# matplotlib基础绘图 2\n",
    "## 直方图\n",
    "### 基础绘图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip uninstall matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/sample_data/jacksboro_fault_dem.npz'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-9cd8149d018f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mdem\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_sample_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'jacksboro_fault_dem.npz'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp_load\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      9\u001b[0m \u001b[0mz\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdem\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'elevation'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0mnrows\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mncols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mz\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.8/site-packages/matplotlib/cbook/__init__.py\u001b[0m in \u001b[0;36mget_sample_data\u001b[0;34m(fname, asfileobj, np_load)\u001b[0m\n\u001b[1;32m    455\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0msuffix\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'.npy'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'.npz'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    456\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mnp_load\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 457\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    458\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    459\u001b[0m                 warn_deprecated(\n",
      "\u001b[0;32m/opt/anaconda3/lib/python3.8/site-packages/numpy/lib/npyio.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(file, mmap_mode, allow_pickle, fix_imports, encoding)\u001b[0m\n\u001b[1;32m    414\u001b[0m             \u001b[0mown_fid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    415\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 416\u001b[0;31m             \u001b[0mfid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstack\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0menter_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mos_fspath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"rb\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    417\u001b[0m             \u001b[0mown_fid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    418\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/sample_data/jacksboro_fault_dem.npz'"
     ]
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "from matplotlib import cbook\n",
    "from matplotlib import cm\n",
    "from matplotlib.colors import LightSource\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "dem = cbook.get_sample_data('jacksboro_fault_dem.npz', np_load=True)\n",
    "z = dem['elevation']\n",
    "nrows, ncols = z.shape\n",
    "x = np.linspace(dem['xmin'], dem['xmax'], ncols)\n",
    "y = np.linspace(dem['ymin'], dem['ymax'], nrows)\n",
    "x, y = np.meshgrid(x, y)\n",
    "\n",
    "region = np.s_[5:50, 5:50]\n",
    "x, y, z = x[region], y[region], z[region]\n",
    "\n",
    "fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))\n",
    "\n",
    "ls = LightSource(270, 45)\n",
    "# To use a custom hillshading mode, override the built-in shading and pass\n",
    "# in the rgb colors of the shaded surface calculated from \"shade\".\n",
    "rgb = ls.shade(z, cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')\n",
    "surf = ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolors=rgb,\n",
    "                       linewidth=0, antialiased=False, shade=False)\n",
    "ax.set_xticks([])\n",
    "ax.set_yticks([])\n",
    "ax.set_zticks([])\n",
    "fig.savefig(\"surface3d_frontpage.png\", dpi=25) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.12 0.21 0.03 0.12 0.09 0.03]\n",
      "0.6\n",
      "1.6666666666666667\n",
      "1.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "data = [1, 1, 9, 1, 3, 5, 8, 2, 1, 5, 11, 8, 3, 4, 2, 5, 5, 2, 2, 2, 7, 11]\n",
    "n_bins = 6\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar', range=(0, 10),\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.6, ec=\"k\")\n",
    "print(num)  # 频率/组距\n",
    "print(sum(num))  # 频率/组距之和\n",
    "print((max(bins)-min(bins))/n_bins)  # 组距\n",
    "print(sum(num)*(max(bins)-min(bins))/n_bins)  # 频率/组距之和*组距\n",
    "\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('value')\n",
    "plt.xticks(bins, bins)\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(True)\n",
    "\n",
    "plt.savefig(r'figs\\figure1.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习1\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(r\".\\files\\assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "# 将序列的长度分成10组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex1.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 201.   354.6  508.2  661.8  815.4  969.  1122.6 1276.2 1429.8 1583.4\n",
      " 1737. ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习1-答案\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(\"./files/assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "# 将序列的长度分成10组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "n_bins = 10\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar',\n",
    "                                 facecolor='#cc3300', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "print(bins)\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('length')\n",
    "plt.xticks(list(map(int, bins)), list(map(int, bins)))\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(False)\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex1.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习2\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(\"./files/assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "\n",
    "# 将序列的长度按照组距200分组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "plt.savefig('figs/ex2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习2-答案\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(\"./files/assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "\n",
    "# 将序列的长度按照组距200分组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "n_bins = (max(data)-min(data))//200+1\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar',\n",
    "                                 range=(min(data)//200*200, (max(data)//200+1)*200),\n",
    "                                 facecolor='#3300cc', alpha=0.75, rwidth=0.45, ec=\"k\")\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('length')\n",
    "plt.xticks(list(map(int, bins)), list(map(int, bins)))\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(True)\n",
    "# 在上面写你的代码#\n",
    "\n",
    "plt.savefig('figs/ex2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 通过直方图推导概率密度函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.49350649e-05 1.62337662e-04 3.89610390e-04 1.13636364e-03\n",
      " 2.17532468e-03 4.51298701e-03 8.01948052e-03 1.54220779e-02\n",
      " 2.12337662e-02 2.67857143e-02 3.37012987e-02 3.75324675e-02\n",
      " 5.09090909e-02 3.32792208e-02 2.84090909e-02 2.23701299e-02\n",
      " 1.56493506e-02 1.09415584e-02 5.97402597e-03 3.18181818e-03\n",
      " 1.39610390e-03 9.41558442e-04 2.92207792e-04 1.62337662e-04\n",
      " 3.24675325e-05]\n",
      "0.3246753246753248\n",
      "3.08\n",
      "1.0000000000000002\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "input_file = open(r\".\\files\\tree_height.txt\")\n",
    "x = list(map(float, [i for i in input_file]))\n",
    "input_file.close()\n",
    "\n",
    "# example data\n",
    "mu = np.mean(x)  # mean of distribution\n",
    "sigma = np.std(x, ddof=1)  # standard deviation of distribution\n",
    "n_bins = 25\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "# the histogram of the data\n",
    "num, bins, patches = plt.hist(x, n_bins, density=True, histtype='bar',\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "\n",
    "print(num)\n",
    "print(sum(num)) \n",
    "print((max(bins)-min(bins))/n_bins) \n",
    "print(sum(num)*(max(bins)-min(bins))/n_bins) \n",
    "\n",
    "plt.savefig('figs/figure2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "input_file = open(\"./files/tree_height.txt\")\n",
    "x = list(map(float, [i for i in input_file]))\n",
    "input_file.close()\n",
    "\n",
    "# example data\n",
    "mu = np.mean(x)  # mean of distribution\n",
    "sigma = np.std(x, ddof=1)  # standard deviation of distribution\n",
    "n_bins = 25\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "# the histogram of the data\n",
    "num, bins, patches = plt.hist(x, n_bins, density=True, histtype='bar',\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "\n",
    "# add a 'best fit' line\n",
    "#y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *\n",
    "#     np.exp(-0.5 * (1 / sigma * (bins - mu))**2))\n",
    "\n",
    "#plt.plot(bins, y, '--')\n",
    "\n",
    "x1 =np.arange(60,140,1)\n",
    "y1 = ((1 / (np.sqrt(2 * np.pi) * sigma)) *\n",
    "     np.exp(-0.5 * (1 / sigma * (x1 - mu))**2))\n",
    "plt.plot(x1, y1, '--')\n",
    "\n",
    "plt.xlabel('Height')\n",
    "plt.ylabel('Probability density')\n",
    "plt.savefig('figs/figure2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习3\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "with open(\"./files/assembly.fas\", 'r') as infile:\n",
    "    for seq_line in infile:\n",
    "        if seq_line[0] != \">\":\n",
    "            data += [len(seq_line.strip())]\n",
    "\n",
    "# 假设序列长度的分布符合y=c/x+b，绘制密度趋势线\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "plt.savefig('figs/ex3.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n",
      "9\n",
      "1.53 -0.00088\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习3-答案\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "with open(\"./files/assembly.fas\", 'r') as infile:\n",
    "    for seq_line in infile:\n",
    "        if seq_line[0] != \">\":\n",
    "            data += [len(seq_line.strip())]\n",
    "\n",
    "# 假设序列长度的分布符合y=c/x+b，绘制密度趋势线\n",
    "# 在下面写你的代码#\n",
    "n_bins = (max(data)-min(data))//200+1\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar',\n",
    "                                 range=(min(data)//200*200, (max(data)//200+1)*200),\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "\n",
    "b = ((bins[1]+bins[0])*num[0]-(bins[-1]+bins[-2])*num[-1])/(bins[0]+bins[1]-bins[-1]-bins[-2])\n",
    "c = (bins[1]+bins[0])/2*num[0] - b*(bins[1]+bins[0])/2\n",
    "x1 =np.arange(200,1800,1)\n",
    "y = (c/x1 + b)\n",
    "plt.plot(x1, y, '--')\n",
    "print(len(num))\n",
    "print(len(bins))\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('length')\n",
    "plt.xticks(list(map(int, bins)), list(map(int, bins)))\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(True)\n",
    "# 在上面写你的代码#\n",
    "print(c,b)\n",
    "plt.savefig('figs/ex3.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "nucleotides = [\"A\", \"G\", \"C\", \"U\"]\n",
    "\n",
    "counts = [\n",
    "    [606, 1024, 759, 398],\n",
    "    [762, 912, 639, 591], \n",
    "    ]\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "plt.title('RNA nucleotides in the ribosome')\n",
    "plt.xlabel('RNA')\n",
    "plt.ylabel('base count')\n",
    "\n",
    "x1 = [2.3, 4.0, 6.0, 8.0]\n",
    "x2 = [1.5, 3.5, 5.5, 7.5]\n",
    "#x2 = [x - 0.5 for x in x1]\n",
    "\n",
    "plt.xticks([1.75, 3.75, 5.75, 7.75], nucleotides)\n",
    "#plt.xticks([x - 0.25 for x in x1], nucleotides)\n",
    "\n",
    "plt.bar(x1, counts[0], width=0.8, color=\"#99cc33\", label=\"E.coli 23S\")\n",
    "plt.bar(x2, counts[1], width=0.8, color=\"#8080cc\", label=\"T.thermophilus 23S\")\n",
    "\n",
    "plt.legend()\n",
    "plt.axis([1.0, 9.0, 0, 1200])\n",
    "plt.savefig('figs/figure6.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习4\n",
    "# 显示三个样本碱基含量百分比的柱状图\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "nucleotides = [\"A\", \"G\", \"C\", \"U\"]\n",
    "# sample 1, sample 2, sample 3\n",
    "counts = [\n",
    "    [0.217438105, 0.367420165, 0.272335845, 0.142805884],\n",
    "    [0.262396694, 0.314049587, 0.220041322, 0.203512397],\n",
    "    [0.285547786, 0.269230769, 0.233100233, 0.212121212]\n",
    "    ]\n",
    "plt.figure(figsize=(12,7))\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex6.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习4-答案\n",
    "# 显示三个样本碱基含量百分比的柱状图\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "nucleotides = [\"A\", \"G\", \"C\", \"U\"]\n",
    "# sample 1, sample 2, sample 3\n",
    "counts = [\n",
    "    [0.217438105, 0.367420165, 0.272335845, 0.142805884],\n",
    "    [0.262396694, 0.314049587, 0.220041322, 0.203512397],\n",
    "    [0.285547786, 0.269230769, 0.233100233, 0.212121212]\n",
    "    ]\n",
    "plt.figure(figsize=(12,7))\n",
    "# 在下面写你的代码#\n",
    "plt.title('RNA nucleotides in the ribosome')\n",
    "plt.xlabel('RNA')\n",
    "plt.ylabel('base freqs')\n",
    "x2 = [3.0, 6.0, 9.0, 12.0]\n",
    "x1 = [x - 0.5 for x in x2]\n",
    "x3 = [x + 0.5 for x in x2]\n",
    "plt.xticks(x2, nucleotides)\n",
    "plt.bar(x1, counts[0], width=0.5, color=\"#99cc33\", label=\"Sample 1\")\n",
    "plt.bar(x2, counts[1], width=0.5, color=\"#ffcc00\", label=\"Sample 2\")\n",
    "plt.bar(x3, counts[2], width=0.5, color=\"#cc3300\", label=\"Sample 3\")\n",
    "plt.legend()\n",
    "plt.axis([1, 14.0, 0, 0.5])\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex4.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAGrCAYAAADUyMFlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAGPlJREFUeJzt3X2MZXd93/HPF9amKjgeUm94tFmUIlRAxqFbQ4RCTQnUdsCQFgW7FHBrOoFA01AqBWfTGBKpSosIUjCK6wQLqCaGQmPqFPPgkAdCBYS1a8A8BWN5w2YpXrC9G1iSdOHbP/ZaDOOZ34znzs6d3Xm9pKu553fOPedn6+zZt87eube6OwAAwPIeMOsJAADAViaYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDPASa6qzquq/bOeB8CJSjADHEdVdUdVfaeqvrXoceWs5wXA2u2Y9QQAtoHndfcfrLZRVe3o7qOrjd3ffWyk471/gK3IHWaAGamqS6vqf1fVm6vqriSvX2HsAVX1y1W1r6rurKp3VtXpk33sqqquqsuq6i+S/OHgeL9UVd+Y3PV+8aLxn6qq/1NVh6vqq1X1+kXr1rx/gJOVO8wAs/XUJO9K8iNJTknyomXGLp08npnkziTvTHJlkpcs2s8/TvIPknxvheM8PMkZSR6V5GlJbqiqvd39pSTfTvLSJJ9L8qQkN1bVLd39vvuxf4CTljvMAMff+6rqnkWPf7No3YHufkt3H+3u76ww9uIkv9Hdt3f3t5JcnuTiqlp80+P13f3tRftYzn/s7r/p7j9J8v4kP5Mk3f3H3f3Z7v5ed38mybU5FsiLrWX/ACcld5gBjr8XDN7D/NU1jD0yyb5Fy/ty7Pr9sFX2s9jd3f3tJft4ZJJU1VOT/HqO3V0+NcmDkrxnDfME2BbcYQaYrV7D2IEkj1m0fFaSo0m+vsp+FntoVT14yT4OTJ7/bpLrk5zZ3acnuSpJrWGeANuCYAbY+q5N8pqqemxVPSTJf0ry7nV8WsUbqurUqvqJJM/N9+8in5bkru7+66o6N8m/2LCZA5wEvCUD4Pj7/ar67qLlG7v7p+/H66/JsbdPfDTJ30nyoST/9n7O4f8muTvH7iofSfKK7v7iZN3PJXnT5POh/yTJf08ydz/3D3DSqm7/ygYAACvxlgwAABgQzAAAMCCYAQBgQDADAMDAlvyUjDPOOKN37do162kAAHASu+mmm77R3TtX225LBvOuXbuyd+/eWU8DAICTWFXtW30rb8kAAIAhwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgDYhubm5jI3NzfraZwQBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzHCCmJuby9zc3KynAQDbjmAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMLBjtQ2q6pokz01yZ3c/aTL27iSPn2wyl+Se7j5nmdfekeSvknw3ydHu3r1B8wYAgE2xajAneXuSK5O8896B7n7Rvc+r6k1JDg1e/8zu/sZ6JwgAALO0ajB390eratdy66qqkvxMkn+ysdMCAICtYdr3MP9Ekq9395dXWN9JPlxVN1XV/GhHVTVfVXurau/BgwennBYAAGyMaYP5kiTXDtY/vbufkuSCJK+qqmestGF3X93du7t7986dO6ecFgAAbIx1B3NV7Ujyz5K8e6VtuvvA5OedSa5Lcu56jwcAALMwzR3mn0zyxe7ev9zKqnpwVZ127/Mkz0ly6xTHAwCATbdqMFfVtUk+nuTxVbW/qi6brLo4S96OUVWPrKobJosPS/Kxqvp0kj9L8v7u/uDGTR0AAI6/tXxKxiUrjF+6zNiBJBdOnt+e5MlTzg8AAGbKN/0BAMCAYAYA2GYWFhZy+PDhHDp0KLt27crCwsKsp7SlCWYAgG1kYWEh8/Pz6e4kyb59+zI/Py+aBwQzAMA2smfPnhw5cuQHxo4cOZI9e/bMaEZb36q/9AcAwMaqN9TsDr5vheF9+2Y2r76iZ3LctXKHGQBgOzn9fo4jmAEAtpVnJTllydgpk3GW5S0ZAADbydmTn783+Xl6jsXy2ctvjjvMAADbz9lJHjR5vCZieRWCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBoCT2NzcXObm5mY9DTihCWYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAZWDeaquqaq7qyqWxeNvb6q/rKqbpk8LlzhtedX1Zeq6raqet1GThy2k4WFhRw+fDiHDh3Krl27srCwMOspAScA1w7YGGu5w/z2JOcvM/7m7j5n8rhh6cqqemCStya5IMkTklxSVU+YZrKwHS0sLGR+fj7dnSTZt29f5ufn/cUHDLl2wMZZNZi7+6NJ7lrHvs9Nclt3397df5vkXUmev479wLa2Z8+eHDly5AfGjhw5kj179sxoRsCJwLUDNs6OKV776qp6aZK9SV7b3XcvWf+oJF9dtLw/yVNX2llVzSeZT5KzzjprimnBxqs31OwOvm+F4X37ZjavvqJnclw40bh2fJ/rxhZ0+awncOJY7y/9/VaSH01yTpKvJXnTMtss96dxxT8t3X11d+/u7t07d+5c57TgJHT6/RwHSFw7YAOtK5i7++vd/d3u/l6S386xt18stT/JmYuWH53kwHqOB9vas5KcsmTslMk4wEpcO2DDrCuYq+oRixZ/Osmty2z2qSSPq6rHVtWpSS5Ocv16jgfb2tlJnrdo+fTJ8tmzmQ5wgnDtgA2z6nuYq+raJOclOaOq9ie5Isl5VXVOjr3F4o4kPzvZ9pFJfqe7L+zuo1X16iQfSvLAJNd09+eOy38FnOzOTvL+yfPXzHIiwAnFtQM2xKrB3N2XLDP8thW2PZDkwkXLNyS5z0fOAQDAicI3/QEAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAM7Jj1BACYztzcXJLknnvumfFM2JIun/UE4MTnDjMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGVg3mqrqmqu6sqlsXjb2xqr5YVZ+pquuqam6F195RVZ+tqluqau9GThwAADbDWu4wvz3J+UvGbkzypO4+O8mfJ7l88Ppndvc53b17fVMEAIDZWTWYu/ujSe5aMvbh7j46WfxEkkcfh7kBAMDMbcR7mP91kg+ssK6TfLiqbqqq+dFOqmq+qvZW1d6DBw9uwLQAAGB6UwVzVe1JcjTJwgqbPL27n5LkgiSvqqpnrLSv7r66u3d39+6dO3dOMy0AANgw6w7mqnpZkucmeXF393LbdPeByc87k1yX5Nz1Hg8AAGZhXcFcVecn+cUkF3X3kRW2eXBVnXbv8yTPSXLrctsCAMBWtZaPlbs2yceTPL6q9lfVZUmuTHJakhsnHxl31WTbR1bVDZOXPizJx6rq00n+LMn7u/uDx+W/AgAAjpMdq23Q3ZcsM/y2FbY9kOTCyfPbkzx5qtkBAMCM+aY/AAAYEMwAADAgmAEAYEAwAwDAwKq/9MfmmpubS5Lcc889M54JW87ls54AAGxP7jADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAgTUFc1VdU1V3VtWti8Z+uKpurKovT34+dIXXvmyyzZer6mUbNfGT0cLCQg4fPpxDhw5l165dWVhYmPWUgC3OdQPg+FvrHea3Jzl/ydjrknykux+X5COT5R9QVT+c5IokT01ybpIrVgrr7W5hYSHz8/Pp7iTJvn37Mj8/7y8/YEWuGwCbY03B3N0fTXLXkuHnJ3nH5Pk7krxgmZf+0yQ3dvdd3X13khtz3/AmyZ49e3LkyJEfGDty5Ej27NkzoxkBW53rBsDm2DHFax/W3V9Lku7+WlX9yDLbPCrJVxct75+M3UdVzSeZT5KzzjprimmtX72hZnLcJMm+FYb37ZvZvPqKnslx4UQzs2uH6wbApjjev/S33BV72atpd1/d3bu7e/fOnTuP87S2oNPv5ziA6wbAppgmmL9eVY9IksnPO5fZZn+SMxctPzrJgSmOefJ6VpJTloydMhkHWI7rBsCmmCaYr09y76devCzJ/1xmmw8leU5VPXTyy37PmYyx1NlJnrdo+fTJ8tmzmQ5wAnDdANgUa/1YuWuTfDzJ46tqf1VdluTXkzy7qr6c5NmT5VTV7qr6nSTp7ruS/FqST00evzoZYzlnJ3nQ5PGa+EsPWJ3rBsBxt6Zf+uvuS1ZYdZ9/+OvuvUlevmj5miTXrGt2AAAwY77pDwAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAAztmPQGWuHzWEwAAYDF3mAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMrDuYq+rxVXXLosfhqvqFJducV1WHFm3zK9NPGQAANs+6P4e5u7+U5JwkqaoHJvnLJNcts+mfdvdz13scAACYpY16S8azknylu/dt0P4AAGBL2KhgvjjJtSus+/Gq+nRVfaCqnrjSDqpqvqr2VtXegwcPbtC0AABgOlMHc1WdmuSiJO9ZZvXNSR7T3U9O8pYk71tpP919dXfv7u7dO3funHZaAACwITbiDvMFSW7u7q8vXdHdh7v7W5PnNyQ5parO2IBjAgDAptiIYL4kK7wdo6oeXlU1eX7u5Hjf3IBjAgDAplj3p2QkSVX93STPTvKzi8ZekSTdfVWSFyZ5ZVUdTfKdJBd3d09zTAAA2ExTBXN3H0ny95aMXbXo+ZVJrpzmGAAAMEu+6Q8AAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwMCOWU8AgCldPusJAJzc3GEGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBg6mCuqjuq6rNVdUtV7V1mfVXVb1bVbVX1map6yrTHBACAzbJjg/bzzO7+xgrrLkjyuMnjqUl+a/ITAAC2vM14S8bzk7yzj/lEkrmqesQmHBcAAKa2EcHcST5cVTdV1fwy6x+V5KuLlvdPxn5AVc1X1d6q2nvw4MENmBYAAExvI4L56d39lBx768WrquoZS9bXMq/p+wx0X93du7t7986dOzdgWgAAML2pg7m7D0x+3pnkuiTnLtlkf5IzFy0/OsmBaY8LAACbYapgrqoHV9Vp9z5P8pwkty7Z7PokL518WsbTkhzq7q9Nc1wAANgs035KxsOSXFdV9+7rd7v7g1X1iiTp7quS3JDkwiS3JTmS5F9NeUwAANg0UwVzd9+e5MnLjF+16HknedU0xwEAgFnxTX8AADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAysO5ir6syq+qOq+kJVfa6q/t0y25xXVYeq6pbJ41emmy4AAGyuHVO89miS13b3zVV1WpKbqurG7v78ku3+tLufO8VxAABgZtZ9h7m7v9bdN0+e/1WSLyR51EZNDAAAtoINeQ9zVe1K8mNJPrnM6h+vqk9X1Qeq6omDfcxX1d6q2nvw4MGNmBYAAExt6mCuqock+R9JfqG7Dy9ZfXOSx3T3k5O8Jcn7VtpPd1/d3bu7e/fOnTunnRYAAGyIqYK5qk7JsVhe6O7fW7q+uw9397cmz29IckpVnTHNMQEAYDNN8ykZleRtSb7Q3b+xwjYPn2yXqjp3crxvrveYAACw2ab5lIynJ3lJks9W1S2TsV9KclaSdPdVSV6Y5JVVdTTJd5Jc3N09xTEBAGBTrTuYu/tjSWqVba5McuV6jwEAALPmm/4AAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABiYKpir6vyq+lJV3VZVr1tm/YOq6t2T9Z+sql3THA8AADbbuoO5qh6Y5K1JLkjyhCSXVNUTlmx2WZK7u/vvJ3lzkv+83uMBAMAsTHOH+dwkt3X37d39t0neleT5S7Z5fpJ3TJ6/N8mzqqqmOCYAAGyq6u71vbDqhUnO7+6XT5ZfkuSp3f3qRdvcOtlm/2T5K5NtvrHM/uaTzE8WH5/kS+ua2MnhjCT3+X8EcW6wMucGI84PVrLdz43HdPfO1TbaMcUBlrtTvLS+17LNscHuq5NcPcV8ThpVtbe7d896Hmw9zg1W4txgxPnBSpwbazPNWzL2Jzlz0fKjkxxYaZuq2pHk9CR3TXFMAADYVNME86eSPK6qHltVpya5OMn1S7a5PsnLJs9fmOQPe73vAQEAgBlY91syuvtoVb06yYeSPDDJNd39uar61SR7u/v6JG9L8t+q6rYcu7N88UZMehvw1hRW4txgJc4NRpwfrMS5sQbr/qU/AADYDnzTHwAADAhmAAAYEMwztIavFn9GVd1cVUcnn3vNNrGGc+PfV9Xnq+ozVfWRqnrMLObJ5lvDufGKqvpsVd1SVR9b5htYOUmtdm4s2u6FVdVV5aPEtpE1XDsuraqDk2vHLVX18lnMc6vyHuYZmXy1+J8neXaOffzep5Jc0t2fX7TNriQ/lOQ/JLm+u9+7+TNls63x3Hhmkk9295GqemWS87r7RTOZMJtmjefGD3X34cnzi5L8XHefP4v5snnWcm5MtjstyfuTnJrk1d29d7PnyuZb47Xj0iS7F38BHd/nDvPsrPrV4t19R3d/Jsn3ZjFBZmYt58YfdfeRyeIncuxz0Dn5reXcOLxo8cFZ4cuiOOmsem5M/FqS/5LkrzdzcszcWs8PViCYZ+dRSb66aHn/ZAzu77lxWZIPHNcZsVWs6dyoqldV1VdyLIx+fpPmxmytem5U1Y8lObO7/9dmTowtYa1/r/zzyVv93ltVZy6zftsSzLOz5q8NZ9tZ87lRVf8yye4kbzyuM2KrWNO50d1v7e4fTfKLSX75uM+KrWB4blTVA5K8OclrN21GbCVruXb8fpJd3X12kj9I8o7jPqsTiGCenbV8tTjb05rOjar6ySR7klzU3X+zSXNjtu7vdeNdSV5wXGfEVrHauXFakicl+eOquiPJ05Jc7xf/to1Vrx3d/c1Ff5f8dpJ/uElzOyEI5tlZy1eLsz2tem5M/mn1v+ZYLN85gzkyG2s5Nx63aPGnknx5E+fH7AzPje4+1N1ndPeu7t6VY7/7cJFf+ts21nLteMSixYuSfGET57flrfursZnOWr5avKr+UZLrkjw0yfOq6g3d/cQZTptNsMavnX9jkockeU9VJclfdPdFM5s0m2KN58arJ//68P+S3J3kZbObMZtljecG29Qaz4+fn3yyztEkdyW5dGYT3oJ8rBwAAAx4SwYAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAAD/x8xYVRhwU97UAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "x1 = [0.1, 0.2, 0.3, 0.4, 0.5]\n",
    "y1 = [10, 15, 10, 15, 17]\n",
    "err1 = (2, 3, 4, 1, 2)\n",
    "width = 0.05\n",
    "plt.bar(x1, y1, width, color='g', yerr=err1, ecolor=\"black\")\n",
    "plt.errorbar(x1, y1, err1, fmt='ko')\n",
    "plt.title('Error bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 箱线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Random test data\n",
    "np.random.seed(2018)\n",
    "all_data = [np.random.normal(0, std, size=100) for std in range(1, 4)]\n",
    "labels = ['x1', 'x2', 'x3']\n",
    "plt.figure(figsize=(12,7))\n",
    "bplot1=plt.boxplot(all_data,\n",
    "                         vert=True,  # vertical box alignment\n",
    "                         patch_artist=True,  # fill with color\n",
    "                         labels=labels)  # will be used to label x-ticks\n",
    "colors = ['pink', 'lightblue', 'lightgreen']\n",
    "for patch, color in zip(bplot1['boxes'], colors):\n",
    "    patch.set_facecolor(color)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Random test data\n",
    "np.random.seed(2018)\n",
    "all_data = [np.random.normal(0, std, size=100) for std in range(1, 4)]\n",
    "labels = ['x1', 'x2', 'x3']\n",
    "\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 7))\n",
    "\n",
    "# rectangular box plot\n",
    "bplot1 = axes[0].boxplot(all_data,\n",
    "                         vert=True,  # vertical box alignment\n",
    "                         patch_artist=True,  # fill with color\n",
    "                         labels=labels)  # will be used to label x-ticks\n",
    "axes[0].set_title('Rectangular box plot')\n",
    "colors = ['pink', 'lightblue', 'lightgreen']\n",
    "for patch, color in zip(bplot1['boxes'], colors):\n",
    "    patch.set_facecolor(color)\n",
    "\n",
    "# notch shape box plot\n",
    "x1 = [0.1, 0.2, 0.3, 0.4, 0.5]\n",
    "y1 = [10, 15, 10, 15, 17]\n",
    "err1 = (2, 3, 4, 1, 2)\n",
    "\n",
    "width = 0.05\n",
    "axes[1].bar(x1, y1, width, color='g', yerr=err1, ecolor=\"black\")\n",
    "axes[1].errorbar(x1, y1, err1, fmt='ko')\n",
    "axes[1].set_title('Error bar')\n",
    "axes[1].set_xticklabels([\"\", \"x1\", \"\", \"x2\", \"\", \"x3\", \"\", \"Tree4\"])\n",
    "\n",
    "# adding horizontal grid lines\n",
    "for ax in axes:\n",
    "    ax.yaxis.grid(True)\n",
    "    ax.set_xlabel('samples')\n",
    "    ax.set_ylabel('values')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 驱动器 C 中的卷没有标签。\n",
      " 卷的序列号是 5E1B-A9CE\n",
      "\n",
      " C:\\Users\\admin\\Desktop\\Class11 的目录\n",
      "\n",
      "2020/12/18  10:47    <DIR>          .\n",
      "2020/12/18  10:47    <DIR>          ..\n",
      "2019/11/28  19:50             8,196 .DS_Store\n",
      "2020/12/18  08:00    <DIR>          .ipynb_checkpoints\n",
      "2020/12/18  08:00    <DIR>          csv\n",
      "2020/12/18  08:00    <DIR>          figs\n",
      "2020/12/18  08:00    <DIR>          files\n",
      "2020/12/18  10:47           733,700 matplotlab动画.ipynb\n",
      "2020/12/18  10:43           513,979 matplotlib基础绘图2.ipynb\n",
      "2020/12/08  23:28            20,693 numpy入门.ipynb\n",
      "2019/11/27  22:37            17,395 热身练习.ipynb\n",
      "2020/12/14  19:19           595,172 直方图，箱线图和正态分布.pptx\n",
      "               6 个文件      1,889,135 字节\n",
      "               6 个目录 34,803,904,512 可用字节\n"
     ]
    }
   ],
   "source": [
    "!dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjEAAAEKCAYAAADjOgQHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAUQ0lEQVR4nO3de6ykd13H8fenrYVWyiVWVmwXWmRLWAtKPbYgRo5Soa26jUpIqyg1DcuteIFgakoQq394l1u5bEJDQekFYnTVxarYYwOh0AVKabe0riu6W5BSLgXTtKXw9Y95Np2OO+dMt/PMzO/s+5Vsdi6/M/M5k5NvPvPMM8+TqkKSJKk1h807gCRJ0sGwxEiSpCZZYiRJUpMsMZIkqUmWGEmS1CRLjCRJalJvJSbJpUnuSHLTmPuT5C1Jdie5MckpfWWR1CbniKTV9Lkl5j3AGavcfyawqfu3FXhHj1kktek9OEckjdFbiamqa4GvrrLkbOC9NXAd8NgkT+grj6T2OEckreaIOT73ccDeoev7utu+OLowyVYG77I46qijfmTjxo0zCShpdbfddtudVfW9c4zgHJEa93DmyDxLzMSqahuwDWBpaal27tw550SSAJL817wzTMo5Ii2mhzNH5vntpNuB4bdCx3e3SdKknCPSIWyeJWY78KvdtwueBdxVVf9vE7AkrcI5Ih3Cevs4KcnlwDJwbJJ9wO8C3wVQVe8EdgBnAbuBu4Ff6yuLpDY5RyStprcSU1XnrnF/Aa/q6/kltc85Imk1HrFXkiQ1yRIjSZKaZImRJElNssRIkqQmWWIkSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU2yxEiSpCZZYiRJUpMsMZIkqUmWGEmS1CRLjCRJapIlRpIkNckSI0mSmmSJkSRJTbLESJKkJlliJElSkywxkiSpSZYYSZLUJEuMJElqkiVGkiQ1yRIjSZKaZImRJElNssRIkqQmWWIkSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU3qtcQkOSPJrUl2J7nwAPc/Mck1ST6d5MYkZ/WZR1J7nCOSxumtxCQ5HLgEOBPYDJybZPPIstcDV1XVM4FzgLf3lUdSe5wjklbT55aYU4HdVbWnqu4DrgDOHllTwKO7y48BvtBjHkntcY5IGuuIHh/7OGDv0PV9wGkja94I/FOSVwPfDZx+oAdKshXYCrBhwwZWVlamnVXSYnKOSBqrzxIziXOB91TVnyV5NvC+JCdX1XeGF1XVNmAbwNLSUi0vL88+qaRF5RyRDlF9fpx0O7Bx6Prx3W3DzgeuAqiqjwGPBI7tMZOktjhHJI3VZ4m5HtiU5MQkRzLY4W77yJr/Bp4HkORpDIbPl3vMJKktzhFJY/VWYqrqfuAC4GrgFgbfHrg5ycVJtnTLXgu8NMlngMuB86qq+sokqS3OEUmr6XWfmKraAewYue0NQ5d3Ac/pM4OktjlHJI3jEXslSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU2yxEiSpCZZYiRJUpMsMZIkqUmWGEmS1CRLjCRJapIlRpIkNckSI0mSmmSJkSRJTbLESJKkJlliJElSkywxkiSpSZYYSZLUJEuMJElqkiVGkiQ1yRIjSZKaZImRJElNssRIkqQmWWIkSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU2yxEiSpCZZYiRJUpMsMZIkqUm9lpgkZyS5NcnuJBeOWfOiJLuS3Jzk/X3mkdQe54ikcY7o64GTHA5cAvw0sA+4Psn2qto1tGYT8DvAc6rqa0ke31ceSe1xjkhaTZ9bYk4FdlfVnqq6D7gCOHtkzUuBS6rqawBVdUePeSS1xzkiaazetsQAxwF7h67vA04bWXMSQJKPAocDb6yqfxx9oCRbga0AGzZsYGVlpY+8khaPc0TSWH2WmEmffxOwDBwPXJvk6VX19eFFVbUN2AawtLRUy8vLM44paYE5R6RDVJ8fJ90ObBy6fnx327B9wPaq+lZV/SdwG4NhJEngHJG0ij5LzPXApiQnJjkSOAfYPrLmbxi8eyLJsQw2C+/pMZOktjhHJI3VW4mpqvuBC4CrgVuAq6rq5iQXJ9nSLbsa+EqSXcA1wOuq6it9ZZLUFueIpNWkquad4SFZWlqqnTt3zjuGJCDJJ6tqad45HirniLQ4Hs4c8Yi9kiSpSZYYSZLUpIlKTJIPT3KbJI3jHJE0baseJybJI4GjgWOTPA5Id9ejGRyESpJW5RyR1Je1Dnb3MuA3ge8HPskDw+cbwNt6zCVp/XCOSOrFqiWmqt4MvDnJq6vqrTPKJGkdcY5I6stEpx2oqrcm+THghOGfqar39pRL0jrjHJE0bROVmCTvA34AuAH4dndzAQ4fSRNxjkiatklPALkEbK7WjownaZE4RyRN1aTHibkJ+L4+g0ha95wjkqZqra9Y/x2Dzb3HALuSfAK4d//9VbVl3M9KEjhHJPVnrY+T/nQmKSStZ84RSb1Y6yvW/zarIJLWJ+eIpL5M+u2kbzLYHDzsLmAn8Nqq2jPtYJLWF+eIpGmb9NtJbwL2Ae9ncLTNcxh8VfJTwKXAch/hJK0rzhFJUzXpt5O2VNW7quqbVfWNqtoGvKCqrgQe12M+SeuHc0TSVE1aYu5O8qIkh3X/XgTc093nMR8kTcI5ImmqJi0xvwz8CnAH8KXu8ouTHAVc0FM2SeuLc0TSVE167qQ9wM+Nufsj04sjab1yjkiatrUOdvfbVfXHSd7KATb3VtWv95ZM0rrgHJHUl7W2xNzS/b+z7yCS1i3niKRerHWwu7/r/r8MIMnRVXX3LIJJWh+cI5L6MtGOvUmenWQX8Lnu+g8leXuvySStK84RSdM26beT3gS8APgKQFV9BviJvkJJWpecI5KmatISQ1XtHbnp21POImmdc45ImqZJTzuwN8mPAZXku4Df4IGd9SRpEs4RSVM16ZaYlwOvAo4Dbgd+uLsuSZNyjkiaqkkPdncng6NtStJBcY5Imra1DnZ3wINT7edBqiStxTkiqS9rbYkZPjjV7wG/22MWSeuTc0RSL9Y62N1l+y8n+c3h65I0CeeIpL5M/BVrVtkcLEkTco5ImpqHUmIkSZIWxlo79n6TB945HZ3kG/vvAqqqHt1nOEntc45I6sta+8QcM6sgktYn54ikvvT6cVKSM5LcmmR3kgtXWfeLSSrJUp95JLXHOSJpnN5KTJLDgUuAM4HNwLlJNh9g3TEMDj/+8b6ySGqTc0TSavrcEnMqsLuq9lTVfcAVwNkHWPf7wB8B9/SYRVKbnCOSxpr0BJAH4zhg+Iy1+4DThhckOQXYWFX/kOR14x4oyVZgK8CGDRtYWVmZflpJi8g5ImmsPkvMqpIcBvw5cN5aa6tqG7ANYGlpqZaXl3vNJqkNzhHp0Nbnx0m3AxuHrh/f3bbfMcDJwEqSzwPPAra7U56kIc4RSWP1WWKuBzYlOTHJkcA5wPb9d1bVXVV1bFWdUFUnANcBW6pq54EfTtIhyDkiaazeSkxV3Q9cAFwN3AJcVVU3J7k4yZa+nlfS+uEckbSaXveJqaodwI6R294wZu1yn1kktck5Imkcz50kSZKaZImRJElNssRIkqQmWWIkSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU2yxEiSpCZZYiRJUpMsMZIkqUmWGEmS1CRLjCRJapIlRpIkNckSI0mSmmSJkSRJTbLESJKkJlliJElSkywxkiSpSZYYSZLUJEuMJElqkiVGkiQ1yRIjSZKaZImRJElNssRIkqQmWWIkSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU3qtcQkOSPJrUl2J7nwAPe/JsmuJDcm+XCSJ/WZR1J7nCOSxumtxCQ5HLgEOBPYDJybZPPIsk8DS1X1DOCDwB/3lUdSe5wjklbT55aYU4HdVbWnqu4DrgDOHl5QVddU1d3d1euA43vMI6k9zhFJYx3R42MfB+wdur4POG2V9ecDHzrQHUm2AlsBNmzYwMrKypQiSlpwzhFJY/VZYiaW5MXAEvDcA91fVduAbQBLS0u1vLw8u3CSmuAckQ49fZaY24GNQ9eP7257kCSnAxcBz62qe3vMI6k9zhFJY/W5T8z1wKYkJyY5EjgH2D68IMkzgXcBW6rqjh6zSGqTc0TSWL2VmKq6H7gAuBq4Bbiqqm5OcnGSLd2yPwEeBXwgyQ1Jto95OEmHIOeIpNX0uk9MVe0Adozc9oahy6f3+fyS2ucckTSOR+yVJElNssRIkqQmWWIkSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU2yxEiSpCZZYiRJUpMsMZIkqUmWGEmS1CRLjCRJapIlRpIkNckSI0mSmmSJkSRJTbLESJKkJlliJElSkywxkiSpSZYYSZLUJEuMJElqkiVGkiQ1yRIjSZKaZImRJElNssRIkqQmWWIkSVKTLDGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkppkiZEkSU2yxEiSpCZZYiRJUpN6LTFJzkhya5LdSS48wP2PSHJld//Hk5zQZx5J7XGOSBqntxKT5HDgEuBMYDNwbpLNI8vOB75WVU8B/gL4o77ySGqPc0TSavrcEnMqsLuq9lTVfcAVwNkja84GLusufxB4XpL0mElSW5wjksY6osfHPg7YO3R9H3DauDVVdX+Su4DvAe4cXpRkK7C1u3pvkpt6SdyvYxn5vRrQYmYw9yw9tefHd448WIt/Iy1mBnPP0kHPkT5LzNRU1TZgG0CSnVW1NOdID1mLuVvMDOaepSQ7551hUs6R+WgxM5h7lh7OHOnz46TbgY1D14/vbjvgmiRHAI8BvtJjJkltcY5IGqvPEnM9sCnJiUmOBM4Bto+s2Q68pLv8QuBfq6p6zCSpLc4RSWP19nFS99n0BcDVwOHApVV1c5KLgZ1VtR14N/C+JLuBrzIYUGvZ1lfmnrWYu8XMYO5Z6jWzc+T/aTF3i5nB3LN00JnjGxZJktQij9grSZKaZImRJElNWtgS0+KhxifI/Joku5LcmOTDSZ40j5yj1so9tO4Xk1SShfj63iS5k7yoe81vTvL+WWc8QJ61/kaemOSaJJ/u/k7OmkfOUUkuTXLHuGOrZOAt3e91Y5JTZp3xQJwjs+McmZ0W50hvM6SqFu4fgx34/gN4MnAk8Blg88iaVwLv7C6fA1zZQOafBI7uLr9i3pknzd2tOwa4FrgOWGohN7AJ+DTwuO764xvIvA14RXd5M/D5eb/WXZafAE4Bbhpz/1nAh4AAzwI+vgCZnSMLlLtb5xyZTeaFmyN9zZBF3RLT4qHG18xcVddU1d3d1esYHPNi3iZ5rQF+n8E5ae6ZZbhVTJL7pcAlVfU1gKq6Y8YZR02SuYBHd5cfA3xhhvnGqqprGXzzZ5yzgffWwHXAY5M8YTbpxnKOzI5zZHaanCN9zZBFLTEHOtT4cePWVNX9wP5Djc/LJJmHnc+gdc7bmrm7zXobq+ofZhlsDZO83icBJyX5aJLrkpwxs3QHNknmNwIvTrIP2AG8ejbRHraH+vc/C86R2XGOzM56nSMHNUOaOO3AepPkxcAS8Nx5Z1lLksOAPwfOm3OUg3EEg03BywzerV6b5OlV9fW5plrducB7qurPkjybwfFPTq6q78w7mBaLc2RmnCMLbFG3xLR4qPFJMpPkdOAiYEtV3TujbKtZK/cxwMnASpLPM/iscvsC7JQ3yeu9D9heVd+qqv8EbmMwjOZlksznA1cBVNXHgEcyOKHbopvo73/GnCOz4xyZnfU6Rw5uhsx7Z58xO/gcAewBTuSBHZd+cGTNq3jwDnlXNZD5mQx2yNo079f4oeQeWb/CYuyQN8nrfQZwWXf5WAabKr9nwTN/CDivu/w0Bp9lZ96vd5fnBMbvlPczPHinvE8sQF7nyALlHlnvHOk380LOkT5myFx/oTV+2bMYNN7/AC7qbruYwTsPGDTLDwC7gU8AT24g878AXwJu6P5tn3fmSXKPrF2I4TPh6x0Gm7B3AZ8Fzmkg82bgo91gugF4/rwzd7kuB74IfIvBO9PzgZcDLx96rS/pfq/PNvQ34hyZUe6Rtc6RfjMv3Bzpa4Z42gFJktSkRd0nRpIkaVWWGEmS1CRLjCRJapIlRpIkNckSI0mSmmSJ0cSSXNSdxfXGJDckOa3H51pZgANhSZoy54imydMOaCLdoat/Fjilqu5NciyDAy1J0kScI5o2t8RoUk8A7qzuEOdVdWdVfSHJG5Jcn+SmJNv2nwG4ewf0F0l2JrklyY8m+esk/57kD7o1JyT5XJK/6tZ8MMnRo0+c5PlJPpbkU0k+kORR3e1/mGRX947uT2f4Wkg6OM4RTZUlRpP6J2BjktuSvD3J/pPOva2qfrSqTgaOYvAua7/7qmoJeCfwtwwO8X4ycF6S/WcKfirw9qp6GvAN4JXDT9q9U3s9cHpVnQLsBF7T/fzPMzjc9jOAP+jhd5Y0Xc4RTZUlRhOpqv8FfgTYCnwZuDLJecBPJvl4ks8CPwX84NCPbe/+/yxwc1V9sXsHtocHTvS1t6o+2l3+S+DHR576WXSH0E5yA/AS4EnAXcA9wLuT/AJw99R+WUm9cI5o2twnRhOrqm8zOOfJSjdsXgY8g8E5LvYmeSODc9Hst//sut8Zurz/+v6/vdHzXoxeD/DPVXXuaJ4kpwLPA14IXMBg+ElaYM4RTZNbYjSRJE9NMnz6+R8Gbu0u39l9vvzCg3joJ3Y7+wH8EvCRkfuvA56T5Cldju9OclL3fI+pqh3AbwE/dBDPLWmGnCOaNrfEaFKPAt6a5LHA/QzO+rsV+DpwE/A/wPUH8bi3Aq9KcimDs8S+Y/jOqvpyt7n58iSP6G5+PfBN4G+TPJLBu6zXHMRzS5ot54imyrNYa26SnAD8fbcznyQ9ZM6RQ5sfJ0mSpCa5JUaSJDXJLTGSJKlJlhhJktQkS4wkSWqSJUaSJDXJEiNJkpr0f6irRtRY2KnLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 648x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习5\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "all_data = [[], [], [], []]\n",
    "labels = [\"Tree1\", \"Tree2\", \"Tree3\", \"Tree4\"]\n",
    "for i in range(1,5):\n",
    "    input_file = open(\"./files/tree_\"+str(i)+\".txt\")\n",
    "    all_data[i-1] = list(map(float, [i for i in input_file]))\n",
    "    input_file.close()\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 7))\n",
    "\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "# adding horizontal grid lines\n",
    "for ax in axes:\n",
    "    ax.yaxis.grid(True)\n",
    "    ax.set_xlabel('Samples')\n",
    "    ax.set_ylabel('Height')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习5-答案\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "all_data = [[], [], [], []]\n",
    "labels = [\"Tree1\", \"Tree2\", \"Tree3\", \"Tree4\"]\n",
    "for i in range(1,5):\n",
    "    input_file = open(\"./files/tree_\"+str(i)+\".txt\")\n",
    "    all_data[i-1] = list(map(float, [i for i in input_file]))\n",
    "    input_file.close()\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 7))\n",
    "\n",
    "# 在下面写你的代码#\n",
    "bplot1 = axes[0].boxplot(all_data,\n",
    "                         vert=True,  # vertical box alignment\n",
    "                         patch_artist=True,  # fill with color\n",
    "                         labels=labels)  # will be used to label x-ticks\n",
    "axes[0].set_title('Four trees\\' height')\n",
    "colors = ['pink', 'lightblue', 'lightgreen', 'lightgray']\n",
    "for patch, color in zip(bplot1['boxes'], colors):\n",
    "    patch.set_facecolor(color)\n",
    "\n",
    "\n",
    "x1 = [1, 2, 3, 4]\n",
    "y1 = [np.mean(all_data[0]), np.mean(all_data[1]),\n",
    "      np.mean(all_data[2]), np.mean(all_data[3])]\n",
    "err1 = [np.std(all_data[0], ddof=1), np.std(all_data[1], ddof=1),\n",
    "        np.std(all_data[2], ddof=1), np.std(all_data[3], ddof=1)]\n",
    "\n",
    "width = 0.5\n",
    "axes[1].bar(x1, y1, width, color='g', yerr=err1, ecolor=\"black\")\n",
    "axes[1].errorbar(x1, y1, err1, fmt='ko')\n",
    "\n",
    "axes[1].set_title('Four trees\\' height')\n",
    "axes[1].set_xticklabels([\"\", \"Tree1\", \"\", \"Tree2\", \"\", \"Tree3\", \"\", \"Tree4\"])\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "# adding horizontal grid lines\n",
    "for ax in axes:\n",
    "    ax.yaxis.grid(True)\n",
    "    ax.set_xlabel('Samples')\n",
    "    ax.set_ylabel('Height')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 热图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from matplotlib import cm\n",
    "import csv\n",
    "\n",
    "\n",
    "def draw_heatmap(data, xlabels, ylabels):\n",
    "    cmap = cm.Blues\n",
    "    figure = plt.figure(facecolor='w')\n",
    "    # ax = figure.add_subplot(3, 4, 9) 将画布分割成3行4列，图像画在从左到右从上到下的第9块\n",
    "    ax = figure.add_subplot(1, 1, 1)\n",
    "    ax.set_yticks(range(len(ylabels)))\n",
    "    ax.set_yticklabels(ylabels)\n",
    "    ax.set_xticks(range(len(xlabels)))\n",
    "    ax.set_xticklabels(xlabels)\n",
    "    vmax = data[0][0]\n",
    "    vmin = data[0][0]\n",
    "    for i in data:\n",
    "        for j in i:\n",
    "            if j > vmax:\n",
    "                vmax = j\n",
    "            if j < vmin:\n",
    "                vmin = j\n",
    "    my_map = ax.imshow(data, interpolation='nearest', cmap=cmap, aspect='auto', vmin=vmin, vmax=vmax)\n",
    "    plt.colorbar(mappable=my_map, cax=None, ax=None, shrink=0.5)\n",
    "    plt.xticks(rotation=90)  # 将字体进行旋转\n",
    "    plt.yticks(rotation=360)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "with open(r'.\\csv\\ka.csv','r', newline='') as csv_file_r:\n",
    "    csv_reader = csv.reader(csv_file_r, delimiter=',', quotechar='\"')\n",
    "    x_labels = next(csv_reader)[1:]\n",
    "    x_labels = list(map(lambda x: float(x.replace('X','')), x_labels))\n",
    "    y_data = []\n",
    "    y_labels = []\n",
    "    for row in csv_reader:\n",
    "        y_data.append(list(map(float, row[1:])))\n",
    "        y_labels.append(row[0])\n",
    "    csv_file_r.close()\n",
    "    draw_heatmap(y_data, x_labels, y_labels)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习6\n",
    "import csv\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def heatmap(data, row_labels, col_labels, ax=None,\n",
    "            cbar_kw={}, cbarlabel=\"\", vmin=-10, vmax=10, **kwargs):\n",
    "    # Plot the heatmap\n",
    "    im = ax.imshow(data, **kwargs, interpolation='nearest', aspect='auto', vmin=vmin, vmax=vmax)\n",
    "    # Create colorbar\n",
    "    cbar = ax.figure.colorbar(im, ax=ax, **cbar_kw)\n",
    "    cbar.ax.set_ylabel(cbarlabel, rotation=-90, va=\"bottom\")\n",
    "\n",
    "    # We want to show all ticks...\n",
    "    ax.set_xticks(np.arange(data.shape[1]))\n",
    "    ax.set_yticks(np.arange(data.shape[0]))\n",
    "    # ... and label them with the respective list entries.\n",
    "    ax.set_xticklabels(col_labels)\n",
    "    ax.set_yticklabels(row_labels)\n",
    "\n",
    "    # Let the horizontal axes labeling appear on top.\n",
    "    ax.tick_params(top=True, bottom=False,\n",
    "                   labeltop=True, labelbottom=False)\n",
    "\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=-30, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "\n",
    "    # Turn spines off and create white grid.\n",
    "    for edge, spine in ax.spines.items():\n",
    "        spine.set_visible(False)\n",
    "    ax.set_xticks(np.arange(data.shape[1]+1)-.5, minor=True)\n",
    "    ax.set_yticks(np.arange(data.shape[0]+1)-.5, minor=True)\n",
    "    ax.grid(which=\"minor\", color=\"w\", linestyle='-', linewidth=3)\n",
    "    ax.tick_params(which=\"minor\", bottom=False, left=False)\n",
    "\n",
    "    return im, cbar\n",
    "\n",
    "# 看懂并改造这个文件\n",
    "# 让这个热图变得美观\n",
    "# 试试看能否自定义是否显示热图中的文字\n",
    "\n",
    "# 数据位置\n",
    "value_result = r\".\\csv\\value.csv\"\n",
    "# 第几列是数据\n",
    "x_index = 2\n",
    "# 第几列是Y坐标轴标题\n",
    "label_index = 0\n",
    "# 色轴最大值和最小值\n",
    "v_min, v_max = -15, 15\n",
    "# 配色方案\n",
    "cmcolor = 'rainbow'\n",
    "\n",
    "y_data = []\n",
    "x_data = []\n",
    "y_labels = []\n",
    "with open(value_result, 'r', newline='') as csv_file_r:\n",
    "    csv_reader = csv.reader(csv_file_r, delimiter=',', quotechar='\"')\n",
    "    x_data = list(map(lambda x: x.split(\"_\")[0], next(csv_reader)[x_index:]))\n",
    "    for row in csv_reader:\n",
    "        y_data.append(list(map(lambda x: round(float(x), 2) if x != \"\" else 0, row[x_index:])))\n",
    "        y_labels.append(row[label_index])\n",
    "        main_data = np.array(y_data)\n",
    "fig, ax = plt.subplots(figsize = (12,7))\n",
    "\n",
    "# We want to show all ticks...\n",
    "ax.set_xticks(np.arange(len(x_data)))\n",
    "ax.set_yticks(np.arange(len(y_labels)))\n",
    "# ... and label them with the respective list entries\n",
    "ax.set_xticklabels(x_data)\n",
    "ax.set_yticklabels(y_labels)\n",
    "\n",
    "# Rotate the tick labels and set their alignment.\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "         rotation_mode=\"anchor\")\n",
    "# Loop over data dimensions and create text annotations.\n",
    "for i in range(len(y_labels)):\n",
    "    for j in range(len(x_data)):\n",
    "        text = ax.text(j, i, main_data[i, j],\n",
    "                       ha=\"center\", va=\"center\", color=\"k\")\n",
    "\n",
    "im, cbar = heatmap(main_data, y_labels, x_data, ax=ax, vmin=v_min, vmax=v_max,\n",
    "                   cmap=cmcolor, cbarlabel=\"\")\n",
    "fig.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "import csv\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def heatmap(data, row_labels, col_labels, ax=None,\n",
    "            cbar_kw={}, cbarlabel=\"\", vmin=-10, vmax=10, **kwargs):\n",
    "    # Plot the heatmap\n",
    "    im = ax.imshow(data, **kwargs, interpolation='nearest', aspect='auto', vmin=vmin, vmax=vmax)\n",
    "    # Create colorbar\n",
    "    cbar = ax.figure.colorbar(im, ax=ax, **cbar_kw)\n",
    "    cbar.ax.set_ylabel(cbarlabel, rotation=-90, va=\"bottom\")\n",
    "\n",
    "    # We want to show all ticks...\n",
    "    ax.set_xticks(np.arange(data.shape[1]))\n",
    "    ax.set_yticks(np.arange(data.shape[0]))\n",
    "    # ... and label them with the respective list entries.\n",
    "    ax.set_xticklabels(col_labels)\n",
    "    ax.set_yticklabels(row_labels)\n",
    "\n",
    "    # Let the horizontal axes labeling appear on top.\n",
    "    ax.tick_params(top=True, bottom=False,\n",
    "                   labeltop=True, labelbottom=False)\n",
    "\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=-30, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "\n",
    "    # Turn spines off and create white grid.\n",
    "    for edge, spine in ax.spines.items():\n",
    "        spine.set_visible(False)\n",
    "    ax.set_xticks(np.arange(data.shape[1]+1)-.5, minor=True)\n",
    "    ax.set_yticks(np.arange(data.shape[0]+1)-.5, minor=True)\n",
    "    ax.grid(which=\"minor\", color=\"w\", linestyle='-', linewidth=3)\n",
    "    ax.tick_params(which=\"minor\", bottom=False, left=False)\n",
    "\n",
    "    return im, cbar\n",
    "\n",
    "\n",
    "# 看懂并改造这个文件\n",
    "# 使之能够能够自定义是否显示热图中的文字\n",
    "# 使之能够用命令行的形式生成热图\n",
    "if __name__ == \"__main__\":\n",
    "    # 数据位置\n",
    "    value_result = r\".\\csv\\value.csv\"\n",
    "    # 第几列是数据\n",
    "    x_index = 2\n",
    "    # 第几列是Y坐标轴标题\n",
    "    label_index = 0\n",
    "    # 色轴最大值和最小值\n",
    "    v_min, v_max = -10, 10\n",
    "    # 配色方案\n",
    "    cmcolor = 'bwr'\n",
    "\n",
    "    csv_file_r = open(value_result, 'r', newline='')\n",
    "    csv_reader = csv.reader(csv_file_r, delimiter=',', quotechar='\"')\n",
    "    x_data = list(map(lambda x: x.split(\"_\")[0], next(csv_reader)[x_index:]))\n",
    "    y_data = []\n",
    "    y_labels = []\n",
    "    for row in csv_reader:\n",
    "        y_data.append(list(map(lambda x: round(float(x), 2) if x != \"\" else 0, row[x_index:])))\n",
    "        y_labels.append(row[label_index])\n",
    "    csv_file_r.close()\n",
    "\n",
    "    main_data = np.array(y_data)\n",
    "    fig, ax = plt.subplots(figsize = (12,7))\n",
    "\n",
    "    # We want to show all ticks...\n",
    "    ax.set_xticks(np.arange(len(x_data)))\n",
    "    ax.set_yticks(np.arange(len(y_labels)))\n",
    "    # ... and label them with the respective list entries\n",
    "    ax.set_xticklabels(x_data)\n",
    "    ax.set_yticklabels(y_labels)\n",
    "\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "    # Loop over data dimensions and create text annotations.\n",
    "    for i in range(len(y_labels)):\n",
    "        for j in range(len(x_data)):\n",
    "            text = ax.text(j, i, main_data[i, j],\n",
    "                           ha=\"center\", va=\"center\", color=\"k\")\n",
    "\n",
    "    im, cbar = heatmap(main_data, y_labels, x_data, ax=ax, vmin=v_min, vmax=v_max,\n",
    "                       cmap=cmcolor, cbarlabel=\"\")\n",
    "    fig.tight_layout()\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x1152 with 79 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "==================\n",
    "Colormap reference\n",
    "==================\n",
    "\n",
    "Reference for colormaps included with Matplotlib.\n",
    "\n",
    "This reference example shows all colormaps included with Matplotlib. Note that\n",
    "any colormap listed here can be reversed by appending \"_r\" (e.g., \"pink_r\").\n",
    "These colormaps are divided into the following categories:\n",
    "\n",
    "Sequential:\n",
    "    These colormaps are approximately monochromatic colormaps varying smoothly\n",
    "    between two color tones---usually from low saturation (e.g. white) to high\n",
    "    saturation (e.g. a bright blue). Sequential colormaps are ideal for\n",
    "    representing most scientific data since they show a clear progression from\n",
    "    low-to-high values.\n",
    "\n",
    "Diverging:\n",
    "    These colormaps have a median value (usually light in color) and vary\n",
    "    smoothly to two different color tones at high and low values. Diverging\n",
    "    colormaps are ideal when your data has a median value that is significant\n",
    "    (e.g.  0, such that positive and negative values are represented by\n",
    "    different colors of the colormap).\n",
    "\n",
    "Qualitative:\n",
    "    These colormaps vary rapidly in color. Qualitative colormaps are useful for\n",
    "    choosing a set of discrete colors. For example::\n",
    "\n",
    "        color_list = plt.cm.Set3(np.linspace(0, 1, 12))\n",
    "\n",
    "    gives a list of RGB colors that are good for plotting a series of lines on\n",
    "    a dark background.\n",
    "\n",
    "Miscellaneous:\n",
    "    Colormaps that don't fit into the categories above.\n",
    "\n",
    "\"\"\"\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# Have colormaps separated into categories:\n",
    "# http://matplotlib.org/examples/color/colormaps_reference.html\n",
    "cmaps = [('COLOR MAP', [\n",
    "            'viridis', 'plasma', 'inferno', 'magma',\n",
    "            'Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds',\n",
    "            'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu',\n",
    "            'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn',\n",
    "            'binary', 'gist_yarg', 'gist_gray', 'gray', 'bone', 'pink',\n",
    "            'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia',\n",
    "            'hot', 'afmhot', 'gist_heat', 'copper',\n",
    "            'PiYG', 'PRGn', 'BrBG', 'PuOr', 'RdGy', 'RdBu',\n",
    "            'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic',\n",
    "            'Pastel1', 'Pastel2', 'Paired', 'Accent',\n",
    "            'Dark2', 'Set1', 'Set2', 'Set3',\n",
    "            'tab10', 'tab20', 'tab20b', 'tab20c',\n",
    "            'flag', 'prism', 'ocean', 'gist_earth', 'terrain', 'gist_stern',\n",
    "            'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg', 'hsv',\n",
    "            'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar'])]\n",
    "\n",
    "\n",
    "nrows = max(len(cmap_list) for cmap_category, cmap_list in cmaps)\n",
    "gradient = np.linspace(0, 1, 256)\n",
    "gradient = np.vstack((gradient, gradient))\n",
    "\n",
    "\n",
    "def plot_color_gradients(cmap_category, cmap_list, nrows):\n",
    "    fig, axes = plt.subplots(nrows=nrows, figsize=(8, 16))\n",
    "    axes[0].set_title(cmap_category + ' colormaps', fontsize=14)\n",
    "    fig.subplots_adjust(top=0.97, bottom=0.01, right=0.98, left=0.15)\n",
    "    for ax, name in zip(axes, cmap_list):\n",
    "        ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))\n",
    "        pos = list(ax.get_position().bounds)\n",
    "        x_text = pos[0] - 0.01\n",
    "        y_text = pos[1] + pos[3]/2.\n",
    "        fig.text(x_text, y_text, name, va='center', ha='right', fontsize=10)\n",
    "\n",
    "    # Turn off *all* ticks & spines, not just the ones with colormaps.\n",
    "    for ax in axes:\n",
    "        ax.set_axis_off()\n",
    "\n",
    "\n",
    "for cmap_category, cmap_list in cmaps:\n",
    "    plot_color_gradients(cmap_category, cmap_list, nrows)\n",
    "plt.savefig('figs/map.pdf')\n",
    "plt.show()"
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